Metodi statistici per la stima di profili di rischio personalizzati basati sulla medicina di precisione del cancro nei pazienti oncologici

Precision medicine is beginning to emerge as a well-defined discipline with specific goals, areas of focus, and tailored methodology. Specifically, the primary goal is to discover treatment rules that leverage heterogeneity to improve clinical decision making in a manner that is reproducible, generalizable, and adaptable as needed. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in support of evidence-based, i.e., data-driven, decision making. Precision Medicine allows patients to be discriminated according to their level of risk (e.g. low or high) and identifies subgroups of patients according to their characteristics in order to assign the treatment to those who are likely to benefit. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimens that maximize some cumulative clinical outcome. The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. The present dissertation focuses on the implementation and application of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. I have focused my research activity mainly in the study of the following topics. 1) Statistical methods to analyze continuous biomarkers. Several approaches were considered according to the design of study: from classical approach - median or mean value, percentiles, optimal cut-point identified by means standard receiver operating characteristic (ROC) analysis-to more complex analysis - time-dependent ROC, conditional inferential tree and subpopulation Treatment Effect Pattern (STEPP) method. 2) Statistical methods for time-to-event endpoints. Competing risks occur commonly in medical research. In the analysis of competing risks data, methods of standard survival analysis lead to incorrect and biased results. In the presence of competing risks, data analysis has to be performed including methods to calculate the cumulative incidence of an event of interest, to compare cumulative incidence curves in the presence of competing risks, and to perform competing risks regression analysis. 3) Meta-analysis for synthesizing evidence. 4) An important topic reviews to use of several statistical methods that handle the issue of treatment switching. The contribution aims at assessing tamoxifen treatment effect taking into account treatment switches, in order to provide a robust assessment of treatment effect applying causal inference methods. 5) The last topic deals with the use of population-based registry and administrative databases. The objective of this project is to develop an acceptable claims-based algorithm to identify second breast cancer events during a 10-year follow-up through a record-linkage of two data sources:the Friuli Venezia Giulia population based-cancer registry and the administrative individual-record FVG database.Precision medicine is beginning to emerge as a well-defined discipline with specific goals, areas of focus, and tailored methodology. Specifically, the primary goal is to discover treatment rules that leverage heterogeneity to improve clinical decision making in a manner that is reproducible, generalizable, and adaptable as needed. This endeavor spans a broad range of scientific areas including drug discovery, genetics/genomics, health communication, and causal inference, all in support of evidence-based, i.e., data-driven, decision making. Precision Medicine allows patients to be discriminated according to their level of risk (e.g. low or high) and identifies subgroups of patients according to their characteristics in order to assign the treatment to those who are likely to benefit. Statistics research in precision medicine is broadly focused on methodological development for estimation of and inference for treatment regimens that maximize some cumulative clinical outcome. The process for using statistical inference to establish personalized treatment strategies requires specific techniques for data-analysis that optimize the combination of competing therapies with candidate genetic features and characteristics of the patient and disease. The present dissertation focuses on the implementation and application of statistical methods for establishing optimal treatment rules for personalized medicine and discuss specific examples in various medical contexts with oncology as an emphasis. I have focused my research activity mainly in the study of the following topics. 1) Statistical methods to analyze continuous biomarkers. Several approaches were considered according to the design of study: from classical approach - median or mean value, percentiles, optimal cut-point identified by means standard receiver operating characteristic (ROC) analysis-to more complex analysis - time-dependent ROC, conditional inferential tree and subpopulation Treatment Effect Pattern (STEPP) method. 2) Statistical methods for time-to-event endpoints. Competing risks occur commonly in medical research. In the analysis of competing risks data, methods of standard survival analysis lead to incorrect and biased results. In the presence of competing risks, data analysis has to be performed including methods to calculate the cumulative incidence of an event of interest, to compare cumulative incidence curves in the presence of competing risks, and to perform competing risks regression analysis. 3) Meta-analysis for synthesizing evidence. 4) An important topic reviews to use of several statistical methods that handle the issue of treatment switching. The contribution aims at assessing tamoxifen treatment effect taking into account treatment switches, in order to provide a robust assessment of treatment effect applying causal inference methods. 5) The last topic deals with the use of population-based registry and administrative databases. The objective of this project is to develop an acceptable claims-based algorithm to identify second breast cancer events during a 10-year follow-up through a record-linkage of two data sources:the Friuli Venezia Giulia population based-cancer registry and the administrative individual-record FVG database

Breastfeeding is an additional protective factor for breast cancer among women living in the metropolitan area of Trieste

The role of breastfeeding as protective factor for breast cancer incidence is controversial among scientific literature. The Interdisciplinary Senology Unit of Trieste has analyzed the relation between breast cancer incidence and lactation habits among a total of 4307 Trieste’s women. In this study, the statistical analysis revealed that over having children, the breastfeeding is a further protective factor for breast cancer. In particular, the decrease of breast cancer risk by breastfeeding resulted to be significant for lactation more than 12 months. It is worth noting that breastfeeding resulted protective only for women in childbearing age and it didn’t result to decrease breast cancer risk among post-menopausal women

Routine Cysticotomy and Flushing of the Cystic Duct in Patients with Low Risk of Common Duct Stones: Can It Be Beneficial?

Gallstone disease affects 15\u201320% of the general population and up to 20% of these patients present common bile duct stones. Aim. This observational study reports our experience on routine cysticotomy and flushing of the cystic duct in patients with low risk of common duct stones. Materials and Methods. We analyzed 731 patients who underwent laparoscopic cholecystectomy between September 2013 and September 2015. Results. Patients were preoperatively stratified on the clinical risk; those presenting with low preoperative risk of common bile duct stones were referred to undergo laparoscopic cholecystectomy and routine cysticotomy with bile duct flushing. Patients presenting thick bile sludge, solid debrides, and/or increased tension of bile outflow underwent unplanned cholangiography. No intraoperative complications or conversion to open technique occurred. Average follow-up time was 22,8 months (range 12 to 37). Rate of retained ductal stones accounted for 0,3%. Conclusions. Routine cysticotomy and bile flushing in our experience is a valid, simple, and not time consumingmanoeuvre that can help decompressing and flushing CBD.Moreover, it is a valid tool for extending selective IOC approach in a focused manner. Further evaluations have to be conducted to evaluate risks and effectiveness of this manoeuvre

Breastfeeding: a reproductive factor able to reduce the risk of luminal B breast cancer in premenopausal White women

In the medical literature, the role of breastfeeding and reproductive factors in the risk of breast carcinoma is still an open debate in premenopausal women. We highlight the role of breastfeeding and reproductive factors in luminal A and luminal B, the most frequent breast cancers. This case-control study analyzes a White premenopausal population of 286 breast cancer patients, divided into molecular subtypes, and 578 controls matched by age. Multivariate logistic regression models were used to assess the relationships of breastfeeding and other reproductive factors (age at menarche, parity, age at first pregnancy, number of children) with the risk of breast cancers. Among the variables examined, reproductive factors did not alter the risk of cancer, whereas breastfeeding up to 12 months was a significant protective factor against luminal B breast cancer (multivariate odds ratio: 0.22, 95% confidence interval: 0.09-0.59, P=0.002). In contrast, luminal A cases did not significantly correlate with breastfeeding or other reproductive factors. Breastfeeding up to 12 months is strongly protective against the more aggressive luminal B, but not against the less aggressive luminal A breast cancer in premenopausal White women

Meta-analysis on the effect of mild primary hyperparathyroidism and parathyroidectomy upon arterial stiffness

CONTEXT: current data about the cardiovascular manifestations of mild primary hyperparathyroidism (pHPT) are often conflicting. Pulse wave velocity (PWV) is the gold-standard method for assessing aortic stiffness, which predicts cardiovascular morbidity and mortality.OBJECTIVE: Primary outcomes were to investigate if mild pHPT was associated with higher PWV and if parathyroidectomy (PTX) reduced PWV in mild pHPT. Secondary outcome was to investigate blood pressure changes after PTX.DATA SOURCES: PubMed, Google Scholar, SCOPUS, Web of Science, and the Cochrane Library.STUDY SELECTION: Eligible studies included reports of PWV in patients with mild pHPT and controls, or in patients with mild pHPT before and after PTX.DATA EXTRACTION: Two investigators independently identified eligible studies and extracted data. Pooled mean difference (MD) was the summary effect measure. Data were presented in forest plots with outlier and influential case diagnostics.DATA SYNTHESIS: Nine observational studies and one RCT were selected, including 433 patients with mild pHPT, 171 of whom underwent PTX, and 407 controls. PWV was significantly higher in mild pHPT as compared to controls (MD=1.18, 0.67 to 1.68, p<0.0001). Seven studies evaluated the effect of PTX on PWV. PTX significantly reduced PWV (MD= -0.48, -0.88 to -0.07, p=0.022).CONCLUSION: Aortic stiffness is increased in patients with mild pHPT, supporting the notion that also mild pHPT is associated with adverse cardiovascular manifestations. PTX significantly reduced arterial stiffness in mild pHPT, indicating that the benefit of PTX over cardiovascular manifestations should not be dismissed but it deserves further studies

Pediatric Emergency Cases in the First Year of the COVID-19 Pandemic in a Tertiary-Level Emergency Setting

Aim: Emergency cases are uncommon events in the pediatric emergency setting. This study aimed to evaluate the effect of the Coronavirus disease 2019 (COVID-19) pandemic by describing the number and type of pediatric emergency cases that arrived at the pediatric emergency department (PED) of a tertiary-level children's hospital in Italy. Methods: We performed a retrospective study, collecting the main features of pediatric emergency patients who arrived during the first year of the COVID-19 pandemic (March 2020-February 2021) compared to the pre-pandemic period (March 2016-February 2020). Results: During the study period, 112,168 patients were visited at the PED, and 237 (0.21%) were emergency cases, median age of 4 years (IQR: 1-12). In the first year of the pandemic, 42 children were coded as emergency cases compared to 195 (49/year) during the pre-pandemic period. The proportion of emergency cases was stable (0.27% during the COVID-19 period versus 0.20% during the pre-COVID-19 period, p = 0.19). No differences were found regarding the age, gender, hour of arrival, and outcome of patients. We found a significant decrease in the proportion of emergency cases related to respiratory diseases (9/42, 21.4% during the COVID-19 period versus 83/195 during the pre-COVID-19 period (42.6%), p = 0.01). Conclusion: In conclusion, our data suggest that the pandemic had a more significant impact on respiratory emergency cases than on pediatric emergencies in general

Children With Short Stature Display Reduced ACE2 Expression in Peripheral Blood Mononuclear Cells

Background: The cause of short stature remains often unknown. The renin-angiotensin system contributes to growth regulation. Several groups reported that angiotensin-converting enzyme 2 (ACE2)-knockout mice weighed less than controls. Our case-control study aimed to investigate if children with short stature had reduced ACE2 expression as compared to controls, and its significance. Materials and Methods: children aged between 2 and 14 years were consecutively recruited in a University Hospital pediatric tertiary care center. Cases were children with short stature defined as height SD ≤ −2 diagnosed with growth hormone deficiency (GHD) or idiopathic short stature (ISS), before any treatment. Exclusion criteria were: acute diseases, kidney disease, endocrine or autoimmune disorders, precocious puberty, genetic syndromes, SGA history. ACE and ACE2 expression were measured in peripheral blood mononuclear cells, angiotensins were measured by ELISA. Results: Children with short stature displayed significantly lower ACE2 expression, being 0.40 fold induction (0.01-2.27) as compared to controls, and higher ACE/ACE2, with no differences between GHD and ISS. ACE2 expression was significantly and inversely associated with the risk of short stature, OR 0.26 (0.07-0.82), and it had a moderate accuracy to predict it, with an AUC of 0.73 (0.61-0.84). The cutoff of 0.45 fold induction of ACE2 expression was the value best predicting short stature, identifying correctly 70% of the children. Conclusions: Our study confirms the association between the reduction of ACE2 expression and growth retardation. Further studies are needed to determine its diagnostic implications

Percutaneous CT-Guided Renal Cryoablation: Technical Aspects, Safety, and Long-Term Oncological Outcomes in a Single Center

Background and objectives: Cryoablation is emerging as a safe and effective therapeutic option for treating renal cell carcinoma. This study analyzed the safety and long-term oncological outcomes of cryoablation in our center. Materials and methods: Patients who underwent computed tomography (CT)-guided percutaneous cryoablation between February 2011 and June 2020 for one or more clinically localized renal tumors were identified. Technical success and treatment efficacy were assessed. Post-procedural complications were classified according to the Clavien-Dindo system. Recurrence-free survival was determined for biopsy-proven malignant renal tumors. Results: A total of 174 renal tumors, 78 of which were biopsy-proven malignant carcinomas, were treated in 138 patients (97 males and 41 females, mean age: 73 years, range: 43-89 years). Mean tumor size was 2.25 cm and 54.6% of the lesions required a complex approach. Technical success was achieved in 171 out of 174 tumors (98.3%). Primary treatment efficacy was 95.3% and increased to 98.2% when retreats were taken into account. The overall complication rate was 29.8%. No complications of Clavien-Dindo grade III or more were encountered. Median follow-up was 21.92 months (range: 0.02-99.87). Recurrence-free survival was 100% at 1 year, 95.3% (95% CI: 82.1%-98.8%) at 3 years, and 88.6% (95% CI: 71.8%-95.7%) at 5 years. Conclusions: Cryoablation is a safe and effective technique for the treatment of small renal lesions, with no major complications when performed by expert interventional radiologists. The multidisciplinary discussion is essential, especially considering the high number of histologically undetermined lesions. Our long-term oncological outcomes are encouraging and in line with the literature

Serum carcinoembryonic antigen pre-operative level in colorectal cancer: revisiting risk stratification

BackgroundResults Biomarkers may play a role as predictive and prognostic factors in colorectal cancer patients. The aims of the study were to verify the prognostic role of pre-operative serum carcinoembryonic antigen (CEA) level in predicting overall survival and risk of recurrence in a cohort of colorectal cancer patients and to evaluate optimal cut-off values.Methods A retrospective cohort analysis was performed on colorectal cancer patients undergoing elective curative surgery between 2004 and 2019 at an Italian Academic Hospital. Main outcomes were overall survival, disease-free survival at 3-years and risk of local, loco-regional and distant recurrence during follow-up. A receiver operating characteristic (ROC) curve analysis was plotted using CEA pre-operative values and follow-up data in order to estimate the optimal cut-off values.A total of 559 patients were considered. The mean CEA value was 12.1 +/- 54.1 ng/mL, and the median 29.3 (0-4995) ng/mL. The ROC curve analysis identified 12.5 ng/mL as the best CEA cut-off value to predict the risk of metastatic development after surgery in stage I-III colorectal cancer patients, and 10 ng/mL as the best CEA cut-off value to predict overall survival and disease-free survival in stage III-IV patients. These data suggest a stratification of colorectal cancer patients in three classes of risk: a low risk class (CEA &lt;10 ng/mL), a moderate risk class (CEA 10-12.5 ng/mL) and a high risk class (CEA &gt;12.5 ng/mL).Conclusion In conclusion, pre-operative serum CEA measurements could integrate information to enhance patient risk stratification and tailored therapy

Current Status of Fibroblast Growth Factor Receptor-Targeted Therapies in Breast Cancer

Breast cancer (BC) is the most common malignancy and second only to lung cancer in terms of mortality in women. Despite the incredible progress made in this field, metastatic breast cancer has a poor prognosis. In an era of personalized medicine, there is an urgent need for better knowledge of the biology leading to the disease, which can lead to the design of increasingly accurate drugs against patients&rsquo; specific molecular aberrations. Among one of the actionable targets is the fibroblast growth factor receptor (FGFR) pathway, triggered by specific ligands. The Fibroblast Growth Factor Receptors/Fibroblast Growth Factors (FGFRs/FGFs) axis offers interesting molecular targets to be pursued in clinical development. This mini-review will focus on the current knowledge of FGFR mutations, which lead to tumor formation and summarizes the state-of-the-art therapeutic strategies for targeted treatments against the FGFRs/FGFs axis in the context of BC